Monte Carlo Renormalization of the 3-D Ising model: Analyticity and Convergence

We review the assumptions on which the Monte Carlo renormalization technique is based, in particular the analyticity of the block spin transformations. On this basis, we select an optimized Kadanoff blocking rule in combination with the simulation of a d=3 Ising model with reduced corrections to scaling. This is achieved by including interactions with second and third neighbors. As a consequence of the improved analyticity properties, this Monte Carlo renormalization method yields a fast convergence and a high accuracy. The results for the critical exponents are y_H=2.481(1) and y_T=1.585(3).Comment: RevTeX, 4 PostScript file

Transverse and longitudinal characterization of electron beams using interaction with optical near-fields

We demonstrate an experimental technique for both transverse and longitudinal characterization of bunched femtosecond free electron beams. The operation principle is based on monitoring of the current of electrons that obtained an energy gain during the interaction with the synchronized optical near-field wave excited by femtosecond laser pulses. The synchronous accelerating/decelerating fields confined to the surface of a silicon nanostructure are characterized using a highly focused sub-relativistic electron beam. Here the transverse spatial resolution of 450 nm and femtosecond temporal resolution achievable by this technique are demonstrated

Pion Mass Effects in the Large NN Limit of \chiPT

We compute the large $N$ effective action of the $O(N+1)/O(N)$ non-linear sigma model including the effect of the pion mass to order $m^2_{\pi}/f_{\pi}^2$. This action is more complex than the one corresponding to the chiral limit not only because of the pion propagators but also because chiral symmetry produce new interactions proportional to $m^2_{\pi}/f_{\pi}^2$. We renormalize the action by including the appropriate counter terms and find the renormalization group equations for the corresponding couplings. Then we estudy the unitarity propierties of the scattering amplitudes. Finally our results are applied to the particular case of the linear sigma model and also are used to fit the pion scattering phase shifts.Comment: FT/UCM/18/9

Symptom complexes in patients with seropositive arthralgia and in patients newly diagnosed with rheumatoid arthritis: a qualitative exploration of symptom development

Objective: The aim of this study was to explore symptoms and symptom development during the earliest phases of rheumatoid arthritis (RA) in patients with seropositive arthralgia and patients newly diagnosed with RA

S-wave Meson-Meson Scattering from Unitarized U(3) Chiral Lagrangians

An investigation of the s-wave channels in meson-meson scattering is performed within a U(3) chiral unitary approach. Our calculations are based on a chiral effective Lagrangian which includes the eta' as an explicit degree of freedom and incorporates important features of the underlying QCD Lagrangian such as the axial U(1) anomaly. We employ a coupled channel Bethe-Salpeter equation to generate poles from composed states of two pseudoscalar mesons. Our results are compared with experimental phase shifts up to 1.5 GeV and effects of the eta' within this scheme are discussed.Comment: 18 pages, 6 figure

The Inverse Amplitude Method in ππ\pi\pi Scattering in Chiral Perturbation Theory to Two Loops

The inverse amplitude method is used to unitarize the two loop $\pi\pi$ scattering amplitudes of SU(2) Chiral Perturbation Theory in the $I=0,J=0$, $I=1,J=1$ and $I=2,J=0$ channels. An error analysis in terms of the low energy one-loop parameters $\bar l_{1,2,3,4,}$ and existing experimental data is undertaken. A comparison to standard resonance saturation values for the two loop coefficients $\bar b_{1,2,3,4,5,6}$ is also carried out. Crossing violations are quantified and the convergence of the expansion is discussed.Comment: (Latex, epsfig) 30 pages, 13 figures, 8 table

Mapping the spatiotemporal dynamics of calcium signaling in cellular neural networks using optical flow

An optical flow gradient algorithm was applied to spontaneously forming net- works of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling with single pixel resolution. Optical flow estimates the direction and speed of motion of objects in an image between subsequent frames in a recorded digital sequence of images (i.e. a movie). Computed vector field outputs by the algorithm were able to track the spatiotemporal dynamics of calcium signaling pat- terns. We begin by briefly reviewing the mathematics of the optical flow algorithm, and then describe how to solve for the displacement vectors and how to measure their reliability. We then compare computed flow vectors with manually estimated vectors for the progression of a calcium signal recorded from representative astrocyte cultures. Finally, we applied the algorithm to preparations of primary astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in order to illustrate the capability of the algorithm for capturing different types of spatiotemporal calcium activity. We discuss the imaging requirements, parameter selection and threshold selection for reliable measurements, and offer perspectives on uses of the vector data.Comment: 23 pages, 5 figures. Peer reviewed accepted version in press in Annals of Biomedical Engineerin

Real-time imputation of missing predictor values in clinical practice

Use of prediction models is widely recommended by clinical guidelines, but usually requires complete information on all predictors that is not always available in daily practice. We describe two methods for real-time handling of missing predictor values when using prediction models in practice. We compare the widely used method of mean imputation (M-imp) to a method that personalizes the imputations by taking advantage of the observed patient characteristics. These characteristics may include both prediction model variables and other characteristics (auxiliary variables). The method was implemented using imputation from a joint multivariate normal model of the patient characteristics (joint modeling imputation; JMI). Data from two different cardiovascular cohorts with cardiovascular predictors and outcome were used to evaluate the real-time imputation methods. We quantified the prediction model's overall performance (mean squared error (MSE) of linear predictor), discrimination (c-index), calibration (intercept and slope) and net benefit (decision curve analysis). When compared with mean imputation, JMI substantially improved the MSE (0.10 vs. 0.13), c-index (0.70 vs 0.68) and calibration (calibration-in-the-large: 0.04 vs. 0.06; calibration slope: 1.01 vs. 0.92), especially when incorporating auxiliary variables. When the imputation method was based on an external cohort, calibration deteriorated, but discrimination remained similar. We recommend JMI with auxiliary variables for real-time imputation of missing values, and to update imputation models when implementing them in new settings or (sub)populations.Comment: 17 pages, 6 figures, to be published in European Heart Journal - Digital Health, accepted for MEMTAB 2020 conferenc